Instructor - Advanced GenAI

About Us

Simplilearn is the world’s #1 online Bootcamp provider, enabling learners around the globe with rigorous and highly specialised training offered in partnership with world-renowned universities and leading corporations. We focus on emerging technologies and skills, such as data science, cloud computing, programming, artificial intelligence, cybersecurity, product management, and more—skills that are transforming the global economy. Our training is hands-on and immersive, including live virtual classes, integrated labs and projects, 24x7 support, and a collaborative learning environment. Over two million professionals and 2,000 corporate training organisations across 150 countries have harnessed our award-winning programmes to achieve their career and business goals.

Simplilearn has collaborated with Fullstack Academy to leverage its widespread footprint in the US region and partnerships with top US universities to grow internationally.

Position Overview

The Online Trainer – Advanced Generative AI plays a key role in delivering engaging and impactful learning experiences to adult learners enrolled in our advanced Generative AI programmes.

The trainer will facilitate live online training sessions covering Generative AI, Large Language Models, Prompt Engineering, RAG, LLM Applications, AI APIs, Multimodal AI, AI-powered automation, and emerging Generative AI technologies.

This role involves explaining advanced Generative AI concepts, demonstrating practical applications of LLMs and AI tools, conducting hands-on demonstrations using modern GenAI platforms and frameworks, and connecting technical concepts with real-world business applications.

The ideal candidate should have strong hands-on experience building or implementing LLM-powered applications, RAG pipelines, AI-powered solutions, prompt engineering workflows, multimodal AI applications, AI automation solutions, and enterprise Generative AI use cases.

Classes are delivered 100% online in a synchronous, instructor-led format.

Key Responsibilities

Deliver live online instructor-led training sessions covering Advanced Generative AI, Large Language Models, Prompt Engineering, RAG, AI APIs, LLM applications, and AI-powered automation.

Cover advanced Generative AI topics including:

• Generative AI fundamentals and evolution
• Large Language Models and LLM architectures
• Foundation models and modern LLMs
• Prompt Engineering and advanced prompting techniques
• Structured prompting and prompt optimisation
• System prompts and instruction design
• Retrieval-Augmented Generation (RAG)
• Embeddings and semantic search
• Vector databases and knowledge retrieval
• LLM context windows and context management
• Function calling and tool integration
• LLM APIs and application development
• LLM orchestration
• Fine-tuning and model customisation
• Model evaluation and output quality
• Hallucination mitigation and factuality
• Multimodal Generative AI
• Text, image, audio, and video generation
• AI-powered workflow automation
• Generative AI applications in enterprise environments
• AI coding assistants and developer productivity tools
• Responsible AI, security, privacy, bias, and governance
• Emerging Generative AI technologies and industry trends

Prepare and continuously update:

• Training presentations
• Learning materials
• Practical exercises
• Hands-on activities
• Generative AI demonstrations
• Prompt Engineering exercises
• LLM application demonstrations
• RAG demonstrations
• Real-world business case studies
• Templates and reference materials

Conduct interactive workshops, Q&A sessions, knowledge checks, guided practice, and hands-on demonstrations.

Conduct practical demonstrations using modern Generative AI platforms, frameworks, and tools such as:

• ChatGPT
• Claude
• Gemini
• Microsoft Copilot
• OpenAI APIs
• Anthropic APIs
• Google Gemini APIs
• Hugging Face
• LangChain
• LangGraph
• LlamaIndex
• Vector databases
• RAG frameworks
• AI coding assistants such as GitHub Copilot, Cursor, Claude Code, or similar tools
• Workflow automation platforms

Guide learners through real-world Generative AI scenarios using practical business and industry examples.

Demonstrate how Generative AI can be used to generate, analyse, transform, summarise, and interact with text, documents, images, audio, video, code, and enterprise data.

Demonstrate how LLM applications can be integrated with external data sources, APIs, databases, enterprise systems, and business workflows.

Support learners in developing practical skills for designing, building, evaluating, and implementing Generative AI solutions.

Maintain high learner engagement and instructional quality throughout all sessions.

Stay updated with current Generative AI developments, foundation models, LLM technologies, AI tools, frameworks, multimodal AI capabilities, and emerging industry trends.

Collaborate with internal curriculum teams to continuously improve training content and learner outcomes.

Required Qualifications

• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, Machine Learning, Engineering, or a related field.
• 10+ years of professional experience in Artificial Intelligence, Generative AI, Machine Learning, Data Science, Software Engineering, or related domains.
• Strong hands-on experience designing, developing, implementing, or deploying Generative AI and LLM-powered applications.
• Prior experience delivering online instructor-led training for professionals or adult learners.
• Demonstrated expertise in Generative AI, Large Language Models, Prompt Engineering, RAG, AI APIs, and LLM application development.
• Strong understanding of:
• Generative AI and foundation models
• Large Language Models
• LLM architectures and capabilities
• Prompt Engineering
• Advanced prompting techniques
• RAG architectures
• Embeddings and vector databases
• Semantic search and knowledge retrieval
• Function calling and tool integration
• LLM APIs and integrations
• LLM orchestration
• Context management
• Fine-tuning and model customisation
• LLM evaluation and performance optimisation
• Hallucination mitigation
• Multimodal Generative AI
• AI-powered automation
• Responsible AI, security, privacy, bias, and governance
• Hands-on experience with Generative AI frameworks and platforms such as OpenAI, Claude, Gemini, Hugging Face, LangChain, LangGraph, LlamaIndex, or similar technologies.
• Strong understanding of AI APIs, LLM integration, and enterprise Generative AI applications.
• Excellent communication, presentation, and facilitation skills.

Required Skills

• Strong hands-on expertise in Advanced Generative AI and LLM application development.
• Strong instructional and learner engagement abilities.
• Ability to simplify complex Generative AI and LLM concepts through practical examples and demonstrations.
• Experience building or demonstrating LLM-powered applications, RAG solutions, AI automation workflows, or Generative AI solutions.
• Experience with platforms and frameworks such as OpenAI, Claude, Gemini, Hugging Face, LangChain, LangGraph, LlamaIndex, or similar technologies.
• Strong understanding of Prompt Engineering, RAG, embeddings, vector databases, tool calling, function calling, and LLM orchestration.
• Ability to explain LLM capabilities, limitations, context management, evaluation, and optimisation.
• Strong understanding of Generative AI, Artificial Intelligence, Machine Learning, and modern AI technologies.
• Excellent communication and storytelling skills.
• Experience conducting live virtual training using Zoom, Microsoft Teams, or similar platforms.
• Strong learner engagement, facilitation, and Q&A management skills.
• Ability to conduct interactive, activity-driven learning experiences.
• Ability to connect Generative AI concepts with real-world business use cases.

Preferred Skills

• Experience training professionals, working professionals, or adult learners in Advanced Generative AI, LLMs, or AI applications.
• Experience creating Generative AI training content, exercises, demonstrations, or case studies.
• Hands-on experience developing production-grade LLM applications or enterprise Generative AI solutions.
• Experience implementing RAG pipelines, vector databases, embeddings, and knowledge retrieval systems.
• Experience integrating LLMs with external APIs, databases, enterprise applications, and business systems.
• Experience with multimodal Generative AI applications.
• Experience with AI-powered automation and workflow orchestration.
• Experience using AI coding assistants such as GitHub Copilot, Cursor, Claude Code, or similar tools.
• Experience with Python and AI development environments.
• Familiarity with current and emerging foundation models and Generative AI platforms.
• Experience demonstrating Generative AI use cases across different business functions.
• Strong understanding of responsible AI, AI ethics, security, privacy, bias, and governance.

Key Competencies

• Strong instructional and facilitation skills.
• Excellent Generative AI, LLM, and AI application expertise.
• Strong hands-on understanding of Generative AI technologies and LLM-powered applications.
• Ability to explain complex technical concepts clearly using practical examples.
• Strong understanding of LLMs, Prompt Engineering, RAG, embeddings, vector databases, APIs, and multimodal AI.
• Professional virtual presence.
• Analytical thinking and structured problem-solving.
• Strong learner engagement and mentoring mindset.
• Excellent communication and presentation abilities.
• Ability to demonstrate practical and business-focused Generative AI applications.
• Passion for developing Generative AI capabilities among professionals and learners.

Student Support & Mentorship

Provide individualised learner support during live training sessions and scheduled office hours.

Maintain regular communication regarding learner progress, training expectations, and skill development.

Respond promptly and professionally to learner and internal team communications.

Provide timely, constructive feedback on practical exercises, activities, and learning assessments.

Support learners in applying Generative AI, LLM, Prompt Engineering, RAG, and AI application development concepts to practical business scenarios.

Help learners design and experiment with LLM applications, RAG solutions, AI-powered workflows, and Generative AI use cases through guided practice and hands-on demonstrations.

Performance Monitoring

Evaluate learner progress based on participation, knowledge checks, practical exercises, and hands-on activities.

Maintain accurate records of learner engagement and performance.

Identify learners requiring additional support and collaborate with internal teams to improve learning outcomes.

Contribute to continuous improvement initiatives for training quality and learner success.

Collaboration & Professional Conduct

Adhere to institutional policies and instructional standards.

Foster an inclusive, collaborative, and professional learning environment.

Serve as a mentor and industry role model for learners developing their Generative AI and LLM skills.

Collaborate with instructional staff and curriculum teams to enhance learner experience and training effectiveness.

Represent Simplilearn professionally when interacting with learners, staff, and external stakeholders.

Work Schedule

Part-Time instructors typically work 8–12 hours per week, depending on training schedules.

Each training session is approximately 3 hours in duration.

Sessions are delivered live in a fully online format.

Flexibility for evening and weekend availability is preferred based on learner cohort schedules.

Compensation

The anticipated compensation for this position is $80 per hour, depending on qualifications, experience, and alignment with programme requirements.

Candidates with exceptional Generative AI expertise, strong hands-on LLM application development experience, extensive industry experience, or strong instructional experience are encouraged to apply.

This position is classified as Part-Time, Non-Exempt, and employees will be compensated for all hours worked in accordance with applicable federal, state, and local wage and hour laws.

Equal Employment Opportunity

We are committed to creating an inclusive environment for all employees and applicants. Employment decisions are made without regard to race, colour, religion, sex, gender identity, sexual orientation, national origin, age, disability, veteran status, or any other protected characteristic under applicable law.

Work Authorisation

Applicants must be legally authorised to work in the United States at the time of application and throughout employment.

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